A PyTorch dataset of the eyes found in the OmniArt dataset
OmniArt Eye Dataset
This package provides a dataset of 118,576 painted eyes. These eyes are extracted from about 245,000 paintings from the OmniArt dataset. The dataset provides the eyes as images, the colour of the iris, and metadata from the OmniArt dataset.
The dataset can be used like any other PyTorch dataset. It extends the
ImageFolder class to provide the images and labels/colour and in addition attaches the OmniArt metadata as a dictionary.
The following classes are used, and how many of that class exist in the dataset:
negative class exists to be able to classify non-eye images. It contains samples of primarily noise and facial areas, such as closed eyelids.
The dataset can be used in the following way
import torch import matplotlib.pyplot as plt import numpy as np import torchvision.utils as vutils from torchvision.transforms import transforms from omniart_eye_dataset import OmniArtEyeDataset dataset = OmniArtEyeDataset(transform=transforms.Compose([ transforms.Resize(50), transforms.CenterCrop(50), transforms.ToTensor(), ])) dataloader = torch.utils.data.DataLoader(dataset, batch_size=64, shuffle=True, num_workers=4) # Take 64 random entries images, color, metadata = next(iter(dataloader)) # Plot the entries plt.figure(figsize=(10, 10)) plt.axis("off") plt.title("OmniArt eyes") plt.imshow(np.transpose(vutils.make_grid(images, padding=5, normalize=True), (1, 2, 0))) plt.show()
This dataset has already been used to train a classifier and painted eye generator.
This package is part of a Master's thesis at the University of Amsterdam.
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